Scan AI

Why use AI and how it can benefit your business

Why Use AI?

The best decisions made in any business or organisation are those that are supported by analysis of the data that the company has at its disposal. In most cases, an average business may only ever analyse 10-20% of its data, whether this be sales figures, customer habits, demographic or geographic trends. This is usually because an entire organisation’s data is vast and the compute power and time to achieve more than 20% is too time consuming or costly.

Greater analysis of the data within your organisation allows you to understand what parameters drive your success, or cause you issues - the deeper you analyse the more insight you get and the better decisions, changes and improvements you can make.

Moving to a Data Driven Business Model

The rise of GPU technology delivering hugely parallel compute power and the growth in available data has led to the ability to analyse the majority or even all of an organisation’s data - but crucially in much shorter timeframes than ever before. The huge range of GPU products on the market now enable even a single workstation to add value by rapidly analysing datasets, and with larger budgets the sky is the limit when it comes to GPU-accelerated datacentres. This is why the use of AI and deep learning technologies is in exponential growth within every sector. Read on to select you sector.

Implementing AI Solutions for every industry

An ever-increasing number of businesses are turning to deep learning and AI to solve their greatest challenges, beat the competition and deliver the best solutions to their customers. Whether optimising operations with powerful and fast analytics solutions, enabling more accurate faster diagnoses in healthcare, delivering personalised customer experiences in retail, when powerful AI-driven platforms are integrated into existing workflows, business is improved and industry is transformed. The possibilities are endless - select the industry of interest below, to learn about how AI is being used today, and discover real world case studies.

AI for the Energy Industry

Energy touches every aspect of modern society, from our personal lives to impacting world economies. Today, the industry faces challenges in exploring new resources, reducing costs, maintaining safe conditions for workers and communities, and ensuring reliable energy delivery to customers. There are numerous ways that GPU-accelerated systems can help address these challenges including enhancing the performance of complex geophysical and engineering applications to reduce time to results. The high compute power, massively paralleled processors and high-speed memory of GPUs allow oil and gas companies to visualise and analyse petabytes of well location data in milliseconds, implement advanced algorithms to locate faults in underground structure and use deep learning training on raw seismic trace data to accelerate exploration and discover faults in geology.

Protective Health & Environment

Ensure that proper personal protective equipment (PPE) protocols are followed and safety hazards are identified by using AI to observe equipment, predict and detect failures, and save lives.

Predictive Maintenance

Avoid blackouts, downtimes, and unnecessary maintenance costs by identifying discrepancies in machinery in real time and predicting the remaining useful life of equipment. AI offers the visualisation and analysis of massive volumes of production and sensor data such as pump pressures, flow rates, and temperatures.

Inspection

AI models can be deployed to inspect and identify potential problems in hard to reach areas such as oil rig exteriors, high roofing or remote pipelines. Using drones instead of humans not only improves safety but increases accuracy and speed of fault finding.

GPU-accelerated computing for Energy

Not only does GPU-accelerated computing provide the data processing powers to drive real insight, it can also provide the visualisation capabilities to make analysis easy too. The demonstration video uses nearly 300 million well production records from nearly 1.3 million wells, spanning 20 years of well performance, yet offers the chance to analyse production decline performance, correlations, rate of change and compile formation-based type curves in seconds.

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Case Studies

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EnvirometriX and OpenGeoHub

Learn how OpenGeoHub and EnvirometriX pioneered a global predictive vegetation and soil mapping system using AI technology.

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AI for the Finance Industry

Financial services business face a growing number of challenges - massive datasets, perpetual market fluctuations, the need for swift analysis and rising demand for personalised assistance. Intelligent GPU-accelerated technologies can address critical challenges within the modern financial services industry allowing institutions to boost risk management, make better data-backed decisions, increase security and reduce fraud - all whilst enhancing customer experiences with advances like natural language processing (NLP) being implemented to better tailor business - customer interactions.

Computational Risk

Accurate forecasts are critical for the performance of businesses. An AI platform accelerates the creation of models that help financial experts assess trends, identify risks, and ensure better information for prospective planning.

Accelerated Computing for Trading

Faster processing results in successful trade execution and increased revenue. GPU-powered hardware acceleration decreases latency, allowing operations to remain competitive.

Fraud Detection

The complexity of fraudulent activity, such as payment theft and money laundering, has evolved in proportionate to advancements in technology. Deep learning dramatically reduces false positives in transactional fraud.

GPU-accelerated computing for Finance

A large part of financial services is driven by risk. AI has the ability to create individualised credit scores based on factors such as income, employment opportunity, and credit history, however this can be further enhanced using feature engineering software such as H2O.ai - this takes huge detests and looks for patterns and trends that wouldn’t normally come to the fore thus giving greater insight into potential areas of risk.

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Case Studies

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TurinTech

Learn how TurinTech enables businesses to automatically build accurate and explainable AI that runs faster. The answer is the Evolutionary Optimisation Platform.

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Cognitiv+

With Cognitiv+ Out of the Box Solution, it’s easy to analyse your documents, extract key provisions, save time and mitigates risks involved in document review.

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AI for the Healthcare Industry

The world’s leading health organisations are equipping their doctors and scientists with GPU-accelerated compute systems to drive AI adoption - helping them transform lives and the future of research. With AI, they can tackle interoperable data, meet the increasing demand for personalised medicine and next-generation clinics, develop intelligent applications unique to their workflows, and accelerate areas such as image analysis, scientific research and drug discovery.

Virtual Reality

AI is being employed to develop robotic and virtual theatres so operations can be remotely performed and training given using virtual reality technology.

Imaging and Analytics

AI-driven medical image analysis is being used to increase accuracy and reduce diagnosis times, freeing consultants up to perform more surgeries.

Drug Creation

Deep learning in drug creation can massively speed up the process of discovery by running simulations and decoding data faster.

GPU-accelerated computing for Healthcare

King’s College London is bringing artificial intelligence in medical imaging to the point of care. In contrast to traditional medical testing, which involves sending scans for further analysis by specialists, point of care testing allows the results gained from X-rays, CT scans or MRI to be delivered immediately at the time of the patient-doctor interaction. The work could lead to breakthroughs in classifying stroke and neurological impairments, determining the underlying causes of cancers, as well as recommending the best treatment for patients.

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Case Studies

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Oxford Robotics Institute

Learning to understand objects in images without supervision for robotics applications.

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Bering, iCAIRD and NHSGCC

Learn how AI-powered chest X-ray image diagnosis technology is being adapted to help early identification of COVID-19 cases.

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King’s College London

King’s College London is bringing artificial intelligence in medical imaging allowing the results gained from X-rays, CT or MRI scans to be delivered immediately at the time of the patient-doctor interaction.

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Vet AI

Joii, which was developed in accordance with world-class vets, enables pet owners to make the best choice for their dog or cat.

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TurinTech

Learn how TurinTech enables businesses to automatically build accurate and explainable AI that runs faster. The answer is the Evolutionary Optimisation Platform.

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AI for Manufacturing

The most progressive industrial companies in the world are implementing GPU-accelerated technologies to deploy large-scale AI initiatives. GPU-accelerated computing enables deep learning and AI at industrial scale, letting you take advantage of unprecedented amounts of sensor and operational data to bring down labour costs, reduce product defects, shorten unplanned downtimes, improve transition times, and increase production speed. AI -powered visual analytics is also being used to improve employ safety and compliance when using personal protection equipment (PPE).

Industrial Inspection

NVIDIA GPUs are used to develop the most accurate automated inspection solutions for manufacturing semiconductors, electronics, automotive components, and assemblies.

Predictive Maintenance

GPU-accelerated predictive maintenance solutions are helping industrial companies drive down operational costs by delivering greater accuracy than traditional machine learning-based methods in predicting equipment failure.

Robotics in Manufacturing

AI-enabled smart factories are changing the landscape of manufacturing. This includes everything from compact robots trained in specific tasks and autonomous rovers delivering parts in manufacturing plants to cooperative robots working together with people.

GPU-accelerated computing for Manufacturing

In addition to the AI powered infrastructure, Scan is also able to design and build any industrial PC requirement for your manufacturing environment. Designed to be robust, resistant to dust, shock and extreme temperatures they provide extended lifecycle solutions to compliment your high performance datacentre components.

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Case Studies

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TurinTech

Learn how TurinTech enables businesses to automatically build accurate and explainable AI that runs faster. The answer is the Evolutionary Optimisation Platform.

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AI in Research & Higher Education

Higher education is at the frontlines of major global challenges, training innovators in AI, accelerated computing, and data science. At the same time, institutions need to meet the demand for more flexible, accessible education options. The ability to handle large workloads, increase efficiency, and lower operational costs with centralised infrastructure and computational excellence is key and this can be delivered in any learning environment by using GPU-accelerated AI and high-performance computing (HPC), to enable researchers to leverage modelling, simulation, and experimental datasets to address even the biggest challenges.

Research

Today’s research requires infrastructure that can handle large computational workloads to derive fast and accurate insights from vast amounts of data. Deep learning systems lowers the cost of computing infrastructure and accelerates the performance of HPC and AI applications.

AI Training

Get hands-on training in AI, data science, and accelerated computing to solve real-world problems. Through online courses and instructor-led workshops students can learn the latest techniques for designing and deploying neural networks.

Pre-Trained AI models

Building AI models can be complex and time-consuming but NVIDIA GPU systems are supported by a hub of essential software for deep learning, machine learning, and HPC with pre-trained AI models, model training scripts, and industry-specific software stacks.

GPU-accelerated computing for Higher Education

In order to deliver cutting edge learning in GPU technologies, guaranteed availability of systems for specific workloads is key. Scan has teamed up with Run:AI to develop certified appliances, that have been designed and tested to maximise GPU resource and ensure your entire class of students get the performance they need. Learn more about GPU virtualisation and Run:AI by watching the video.

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Case Studies

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King’s College London

King’s College London is bringing artificial intelligence in medical imaging allowing the results gained from X-rays, CT or MRI scans to be delivered immediately at the time of the patient-doctor interaction.

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FDL Europe 2020 - Clouds and Aerosols

The project team used observations from a geo-stationary satellite over the Southern Atlantic Ocean, combined with data from ECMWF and IMERG estimates to better understand the aerosol impact on cloud structure through the application of multiple machine learning methods.

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FDL Europe 2020 - Digital Twin Earth

The DTE project set out to discover whether machine learning can learn forecast precipitation by fusing simulated satellite weather data with physical model data, to offer a low-cost alternative to expensive simulation infrastructure.

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AI for the Transportation Industry

Autonomous vehicles will transform the way we live, work, and play, creating safer and more efficient roads. With the power of GPU-accelerated systems embedded within vehicles, AI models can be deployed to improve road safety, increase productivity and develop greener transportation. Embedded platforms can simultaneously process data from up a wide array of sensors, constantly collecting vital data for building a robust autonomous driving training library spanning a wide variety of traffic scenarios and conditions - essential for the development of safe self-driving vehicles.

Freedom of Mobility

More than 500 million hearing- or visually-impaired people and a growing ageing population worldwide must rely on others to travel every day.

Give Back Valuable Time

Commuters spend hundreds of hours behind the wheel each year—time that could be used to work, play, or spend time with family.

Improve Road Safety

Traffic crashes cause between 20 to 50 million injuries around the world each year, costing billions in damages and delays.

GPU-accelerated computing for Transportation

Solutions to power autonomous vehicles are complex and made up of many sensors in order to collect and analyse the data in real time. Scan, as a trusted AI advisor can bring together these systems working with partners including NVIDIA and Advantech to deliver complete end to end solutions.

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Case Studies

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TurinTech

Learn how TurinTech enables businesses to automatically build accurate and explainable AI that runs faster. The answer is the Evolutionary Optimisation Platform.

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AI for the Surveillance Industry

Surveillance using multiple sensors at the edge connected to AI-powered analytics has the ability to influence outcomes in a number of environments - retail, warehousing, logistics and entertainment. Leading organisations are leveraging AI to reduce shrinkage, improve forecasting, automate warehouse logistics, determine in-store promotions and real-time pricing, deliver personalisation and recommendations to customers, and deliver better experiences both in stores, theatres, casinos and more.

Asset Protection

Retailers worldwide are losing billions per year to shrinkage, however the use of intelligent video analytics can accurately and efficiently reduce shrinkage.

Store Analytics

In-store data generated from point-of-sale transactions, cameras, and sensors are rife with insights that help determine customer preferences.

Ensuring Public Safety

Retail and entertainment spaces have had to rapidly shift to meet the needs of their customers—accommodating new purchasing behaviours, increased demand, and health safety needs.

GPU-accelerated computing for Surveillance

Surveillance is just the start. When backed by video analytics using anonymous facial detection to identify the age range, gender and dwell times of your customers. Detecting dwell times allows you to gain insights into how customers respond to your advertising and information displays. Gathering age range and gender data lets you learn more about the demographics of your audience. Video Analytics solutions and systems can be applied to digital screens, mannequins, shop ceilings, supermarket aisles or any other strategic points to test consumer behaviour.

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AI for the Smart Cities

AI, powered by GPU-accelerated computing, has the ability to deliver new ways to create more sustainable cities, maintain infrastructure, and improve public services for residents and communities. It all starts with the ability to gather data from trillions of sensors and other IoT devices and extract actionable insights in real time.

Faster Response Time

Process and analyse data in real time to improve operational efficiency, resource allocation, and disaster response.

Secure Deployment & Scalability

Deploy AI from the edge to the cloud with a range of appliances, from the NVIDIA Jetson embedded platform range able to handle an entire city’s sensors.

Traffic Management

Perform realtime traffic flow analysis and re-routing to ensure minimal commuter delays and optimal public transport performance.

GPU-accelerated computing for Smart Cities

Solutions to power large smart city deployments are complex and made up of many hundreds of sensors in order to collect and analyse data in real time. Scan, as a trusted AI advisor can bring together these systems working with partners including Advantech to deliver complete end to end solutions, driven by the SKY range of edge ruggedised AI servers using NVIDIA Tesla T4 GPU cards.

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Case Studies

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TurinTech

Learn how TurinTech enables businesses to automatically build accurate and explainable AI that runs faster. The answer is the Evolutionary Optimisation Platform.

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AI for the Retail Sector

Leading retailers are leveraging AI to reduce shrinkage, improve forecasting, automate warehouse logistics, determine in-store promotions and real-time pricing, enable customer personalisation and recommendations, and deliver better shopping experiences—both in stores and online. Understanding customer behaviour has never been more critical for retailers looking to drive growth. AI applications powered by video analytics can give retailers the same visibility into customer behaviour in stores as they currently have online.

Intelligent Stores

Using data from cameras and sensors, retailers are leveraging AI to reduce shrinkage, eliminate stockout, and gain visibility into customer behaviours. The same infrastructure can also power faster checkouts.

Forecasting & Inventory Management

AI is also improving demand forecasting and inventory management. Demand forecasting uses data from various sources to ensure the right products are available in the right store at the right time.

AI in Warehouse Logistics

Warehouse logistics is the art of optimising, integrating, automating, and managing the flow of products in fulfilment or distribution centres. Combining automation and management in supply chains leads to operational efficiency and higher process throughput.

GPU-accelerated computing for Retail

To complement our market leading AI portfolio, Scan is also the UK provider of Beabloo solutions. Beabloo’s integrated solutions combine digital signage, analytics and automation to help companies optimise the impact of their marketing strategies in retail spaces. Delivering customer tracking, heat maps and other interaction data it can become even more insightful when combined with an AI-driven platform to extract trends even faster.

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Case Studies

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TurinTech

Learn how TurinTech enables businesses to automatically build accurate and explainable AI that runs faster. The answer is the Evolutionary Optimisation Platform.

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Interaction Care

Interaction Care uses a unique combination of technologies to help our clients proactively protect their customers and employees on site from high-risk situations that could jeopardise their health and safety.

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Deep Learning Guide

Now you know how AI and deep learning could help your organisation, why not read on to learn more about the process of deep learning, its terminology, how to prepare your data and where to get started

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